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Dust particles from high latitudes have a potentially large local, regional, and global significance to climate and the environment as short-lived climate forcers, air pollutants, and nutrient sources. Identifying the locations of local dust sources and their emission, transport, and deposition processes is important for understanding the multiple impacts of high-latitude dust (HLD) on the Earth's systems. Here, we identify, describe, and quantify the source intensity (SI) values, which show the potential of soil surfaces for dust emission scaled to values 0 to 1 concerning globally best productive sources, using the Global Sand and Dust Storms Source Base Map (G-SDS-SBM). This includes 64 HLD sources in our collection for the northern (Alaska, Canada, Denmark, Greenland, Iceland, Svalbard, Sweden, and Russia) and southern (Antarctica and Patagonia) high latitudes. Activity from most of these HLD sources shows seasonal character. It is estimated that high-latitude land areas with higher (SI ≥0.5), very high (SI ≥0.7), and the highest potential (SI ≥0.9) for dust emission cover >1 670 000 km2, >560 000 km2, and >240 000 km2, respectively. In the Arctic HLD region (≥60∘ N), land area with SI ≥0.5 is 5.5 % (1 035 059 km2), area with SI ≥0.7 is 2.3 % (440 804 km2), and area with SI ≥0.9 is 1.1 % (208 701 km2). Minimum SI values in the northern HLD region are about 3 orders of magnitude smaller, indicating that the dust sources of this region greatly depend on weather conditions. Our spatial dust source distribution analysis modeling results showed evidence supporting a northern HLD belt, defined as the area north of 50∘ N, with a “transitional HLD-source area” extending at latitudes 50–58∘ N in Eurasia and 50–55∘ N in Canada and a “cold HLD-source area” including areas north of 60∘ N in Eurasia and north of 58∘ N in Canada, with currently “no dust source” area between the HLD and low-latitude dust (LLD) dust belt, except for British Columbia. Using the global atmospheric transport model SILAM, we estimated that 1.0 % of the global dust emission originated from the high-latitude regions. About 57 % of the dust deposition in snow- and ice-covered Arctic regions was from HLD sources. In the southern HLD region, soil surface conditions are favorable for dust emission during the whole year. Climate change can cause a decrease in the duration of snow cover, retreat of glaciers, and an increase in drought, heatwave intensity, and frequency, leading to the increasing frequency of topsoil conditions favorable for dust emission, which increases the probability of dust storms. Our study provides a step forward to improve the representation of HLD in models and to monitor, quantify, and assess the environmental and climate significance of HLD.

Melting of the Greenland Ice Sheet (GrIS) is the largest single contributor to eustatic sea level and is amplified by the growth of pigmented algae on the ice surface, which increases solar radiation absorption. This biological albedo-reducing effect and its impact upon sea level rise has not previously been quantified. Here, we combine field spectroscopy with a radiative-transfer model, supervised classification of unmanned aerial vehicle (UAV) and satellite remote-sensing data, and runoff modelling to calculate biologically driven ice surface ablation. We demonstrate that algal growth led to an additional 4.4–6.0 Gt of runoff from bare ice in the south-western sector of the GrIS in summer 2017, representing 10 %–13 % of the total. In localized patches with high biomass accumulation, algae accelerated melting by up to 26.15±3.77 % (standard error, SE). The year 2017 was a high-albedo year, so we also extended our analysis to the particularly low-albedo 2016 melt season. The runoff from the south-western bare-ice zone attributed to algae was much higher in 2016 at 8.8–12.2 Gt, although the proportion of the total runoff contributed by algae was similar at 9 %–13 %. Across a 10 000 km2 area around our field site, algae covered similar proportions of the exposed bare ice zone in both years (57.99 % in 2016 and 58.89 % in 2017), but more of the algal ice was classed as “high biomass” in 2016 (8.35 %) than 2017 (2.54 %). This interannual comparison demonstrates a positive feedback where more widespread, higher-biomass algal blooms are expected to form in high-melt years where the winter snowpack retreats further and earlier, providing a larger area for bloom development and also enhancing the provision of nutrients and liquid water liberated from melting ice. Our analysis confirms the importance of this biological albedo feedback and that its omission from predictive models leads to the systematic underestimation of Greenland's future sea level contribution, especially because both the bare-ice zones available for algal colonization and the length of the biological growth season are set to expand in the future.

Modelling the development of soils in glacier forefields is necessary in order to assess how microbial and geochemical processes interact and shape soil development in response to glacier retreat. Furthermore, such models can help us predict microbial growth and the fate of Arctic soils in an increasingly ice-free future. Here, for the first time, we combined field sampling with laboratory analyses and numerical modelling to investigate microbial community dynamics in oligotrophic proglacial soils in Svalbard. We measured low bacterial growth rates and growth efficiencies (relative to estimates from Alpine glacier forefields) and high sensitivity of bacterial growth rates to soil temperature (relative to temperate soils). We used these laboratory measurements to inform parameter values in a new numerical model and significantly refined predictions of microbial and biogeochemical dynamics of soil development over a period of roughly 120 years. The model predicted the observed accumulation of autotrophic and heterotrophic biomass. Genomic data indicated that initial microbial communities were dominated by bacteria derived from the glacial environment, whereas older soils hosted a mixed community of autotrophic and heterotrophic bacteria. This finding was simulated by the numerical model, which showed that active microbial communities play key roles in fixing and recycling carbon and nutrients. We also demonstrated the role of allochthonous carbon and microbial necromass in sustaining a pool of organic material, despite high heterotrophic activity in older soils. This combined field, laboratory, and modelling approach demonstrates the value of integrated model–data studies to understand and quantify the functioning of the microbial community in an emerging High Arctic soil ecosystem.

Iceberg-hosted sediments and atmospheric dust transport potentially bioavailable iron to the Arctic and Southern oceans as ferrihydrite. Ferrihydrite is nanoparticulate and more soluble, as well as potentially more bioavailable, than other iron (oxyhydr)oxide minerals (lepidocrocite, goethite, and hematite). A suite of more than 50 iceberg-hosted sediments contain a mean content of 0.076 wt % Fe as ferrihydrite, which produces iceberg-hosted Fe fluxes ranging from 0.7 to 5.5 and 3.2 to 25 Gmoles yr−1 to the Arctic and Southern oceans respectively. Atmospheric dust (with little or no combustion products) contains a mean ferrihydrite Fe content of 0.038 wt % (corresponding to a fractional solubility of ∼ 1 %) and delivers much smaller Fe fluxes (0.02–0.07 Gmoles yr−1 to the Arctic Ocean and 0.0–0.02 Gmoles yr−1 to the Southern Ocean). New dust flux data show that most atmospheric dust is delivered to sea ice where exposure to melting/re-freezing cycles may enhance fractional solubility, and thus fluxes, by a factor of approximately 2.5. Improved estimates for these particulate sources require additional data for the iceberg losses during fjord transit, the sediment content of icebergs, and samples of atmospheric dust delivered to the polar regions.

Recent research suggests that under certain temperature and relative humidity conditions atmospheric aerosol may be present in the form of a glassy solid. In order to understand the impacts that this may have on aerosol–cloud interactions and atmospheric chemistry, knowledge of water diffusion within such aerosol particles is required. Here, a method is described in which Raman spectroscopy is used to observe D2O diffusion in high-viscosity aqueous solutions, enabling a quantitative assessment of water diffusion coefficients, Dwater, as a function of relative humidity. Results for sucrose solutions compare well with literature data at 23.5 ± 0.3 °C, and demonstrate that water diffusion is slow (Dwater ~5 × 10−17 m2 s−1), but not arrested, just below the glass transition at a water activity of 0.2. Room temperature water diffusion coefficients are also presented for aqueous levoglucosan and an aqueous mixture of raffinose, dicarboxylic acids and ammonium sulphate: at low humidity, diffusion is retarded but still occurs on millisecond to second timescales in atmospherically relevant-sized particles. The effect of gel formation on diffusion in magnesium sulfate solutions is shown to be markedly different from the gradual decrease in diffusion coefficients of highly viscous liquids. We show that using the Stokes–Einstein equation to determine diffusion timescales from viscosity leads to values which are more than 5 orders of magnitude too big, which emphasises the need to make measurements of diffusion coefficients. In addition, comparison of bounce fraction data for levoglucosan with measured diffusion data reveals that even when particles bounce the diffusion timescales for water are a fraction of a second for a 100 nm particle. This suggests a high bounce fraction does not necessarily indicate retarded water diffusion.

Physicist James Trefil once describes the universe as "The Spongy Universe," comparing large-scale cosmic structures to the structure of a sponge. The NASA Genesis education module "Cosmic Chemistry: Cosmogony" features the "Spongy Universe" activity in which pairs of students observe a household sponge, making inferences about how the structures and holes in the sponge were made and, by extension, how the structures and voids in the universe may have formed. Because the sponge is such a good model for the universe, the authors of this article modified this "Spongy Universe" activity for use with visually impaired students and pilot tested it at the Colorado School for the Deaf and the Blind. Upon completion of the pilot test, they learned that teachers work more effectively with visually impaired students in the classroom when they achieve three objectives: (1) to help all students "see" with their "mind's eye" when introducing new concepts; (2) to use manipulatives and tactile graphics to help visually impaired students learn abstract concepts; and (3) to use visualization techniques involving familiar things to help students learn new abstract concepts. (Contains 5 figures.)

Observations show that the fractional solubility of Fe (FS-Fe, percentage of dissolved to total Fe) in dust aerosol increases considerably from 0.1 % in regions of high dust mass concentration to 80 % in remote regions where concentrations are low. Here, we combined laboratory geochemical measurements with global aerosol model simulations to test the hypothesis that the increase in FS-Fe is due to physical size sorting during transport. We determined the FS-Fe and fractional solubility of Al (FS-Al) in size-fractionated dust generated from two representative soil samples collected from known Saharan dust source regions using a customized dust re-suspension and collection system. The results show that the FS-Fe is size-dependent and ranges from 0.1–0.3 % in the coarse size fractions (>1 μm) to ~0.2–0.8 % in the fine size fractions (100 μg m−3) to ~0.2 % at low concentrations (–3) due to physical size sorting (i.e., particle gravitational settling). These values are one to two orders of magnitude smaller than those observed on cruises across the tropical and sub-tropical North Atlantic Ocean under an important pathway of Saharan dust plumes for similar dust mass concentrations. Even when the FS-Fe of sub-micrometer size fractions (0.18–0.32 μm, 0.32–0.56 μm, and 0.56–1.0 μm) in the model is increased by a factor of 10 over the measured values, the calculated FS-Fe of the dust is still more than an order of magnitude lower than that measured in the field. Therefore, the physical sorting of dust particles alone is unlikely to be an important factor in the observed inverse relationship between the FS-Fe and FS-Al and the atmospheric mineral dust mass concentrations. The results suggest that processes such as chemical reactions and/or mixing with combustion particles are the main mechanisms to cause the increased FS-Fe in long-range transported dust aerosols.

We investigated the iron (Fe) dissolution kinetics of African (Tibesti) and Asian (Beijing) dust samples at acidic pH with the aim of reproducing the low pH conditions in atmospheric aerosols. The Beijing dust and three size fractions of the Tibesti dust (20; 10; and 2.5) were dissolved at pH 1, 2 and/or 3 for up to 1000 h. In the first 10 min, all dust samples underwent an extremely fast Fe solubilisation. Subsequently, the Fe dissolution proceeded at a much slower rate before reaching a stable dissolution plateau. The time-dependant Fe dissolution datasets were best described by a model comprising three acid-extractable Fe pools each dissolving according to first-order kinetics. The dissolution rate constant k (h−1) of each pool was independent of the source (Saharan or Asian) and the size (PM20, PM10 or PM2.5) of the dust but highly dependent on pH. The "fast" Fe pool had a k (25 h−1 at pH = 1) of a similar magnitude to "dry" ferrihydrite nanoparticles and/or poorly crystalline Fe(III) oxyhydroxide, while the "intermediate" and "slow" Fe pools had k values respectively 50–60 times and 3000–4000 times smaller than the "fast" pool. The "slow" Fe pool was likely to consist of both crystalline Fe oxide phases (i.e., goethite and/or hematite) and Fe contained in the clay minerals. The initial mass of the "fast", "intermediate" and "slow" Fe pools represented respectively about 0.5–2%, 1–3% and 15–40% of the total Fe in the dust samples. Furthermore, we showed that in systems with low dust/liquid ratios, Fe can be dissolved from all three pools, whereas at high dust/liquid ratios (e.g., in aerosols), sufficient Fe may be solubilised from the "fast" phase to dominate the Fe dissolved and to suppress the dissolution of Fe from the other Fe pools. These data demonstrated that dust/liquid ratio and pH are fundamental parameters controlling Fe dissolution kinetics in the dust. In order to reduce errors in atmospheric and climate models, these fundamental controlling factors need to be included.